TY - CHAP
T1 - Automated transportation of microparticles in vivo
AU - Li, Xiaojian
AU - Sun, Dong
PY - 2019/11/30
Y1 - 2019/11/30
N2 - For most biorobotics and biomechatronic researchers, the in vivo applications of biorobotics and biomechatronic have always been one of the most important research goals. The in vivo automated transportation of microparticles is one of the key technologies to achieve in vivo applications, such as drug delivery, cell delivery, thrombus elimination, and cell surgery. In this chapter, an in vivo microparticles transportation system and its related control algorithms are introduced. This system focuses on how to automatically transport the target microparticles to the destination in the dynamic in vivo environment and guarantees the success rate of transportation. First, a close-loop control scheme is established with visual feedback for in vivo transportation. The scheme utilizes image processing techniques, such as background segmentation, threshold segmentation, and Hough transform, and thus can identify microparticles location in complex in vivo environments. Second, based on the close-loop control scheme, a disturbance compensation controller is developed to minimize the influence of the drag force of blood flow. The disturbance compensation controller exhibits advantages in adjusting the trajectory of the cell transport online, trajectory correction, minimizing the steady-state error, and eliminating overshoot and thus can be applied to dynamic in vivo environments. Third, a collision-avoidance vector method is incorporated into the disturbance compensation controller to avoid obstacles during the in vivo transportation of microparticles. This method integrates obstacle detection and collision-avoidance determination into one single step, thereby reducing the online processing time while enhancing the efficiency in obstacle avoidance. Different collision avoidance strategies can be used by adjusting the operator to suit for different transportation environments. The performances of these methods are validated through simulations and experiments of tracking single red blood cells in living zebrafish.
AB - For most biorobotics and biomechatronic researchers, the in vivo applications of biorobotics and biomechatronic have always been one of the most important research goals. The in vivo automated transportation of microparticles is one of the key technologies to achieve in vivo applications, such as drug delivery, cell delivery, thrombus elimination, and cell surgery. In this chapter, an in vivo microparticles transportation system and its related control algorithms are introduced. This system focuses on how to automatically transport the target microparticles to the destination in the dynamic in vivo environment and guarantees the success rate of transportation. First, a close-loop control scheme is established with visual feedback for in vivo transportation. The scheme utilizes image processing techniques, such as background segmentation, threshold segmentation, and Hough transform, and thus can identify microparticles location in complex in vivo environments. Second, based on the close-loop control scheme, a disturbance compensation controller is developed to minimize the influence of the drag force of blood flow. The disturbance compensation controller exhibits advantages in adjusting the trajectory of the cell transport online, trajectory correction, minimizing the steady-state error, and eliminating overshoot and thus can be applied to dynamic in vivo environments. Third, a collision-avoidance vector method is incorporated into the disturbance compensation controller to avoid obstacles during the in vivo transportation of microparticles. This method integrates obstacle detection and collision-avoidance determination into one single step, thereby reducing the online processing time while enhancing the efficiency in obstacle avoidance. Different collision avoidance strategies can be used by adjusting the operator to suit for different transportation environments. The performances of these methods are validated through simulations and experiments of tracking single red blood cells in living zebrafish.
KW - Closed-loop control
KW - Collision avoidance
KW - Disturbance compensation
KW - In vivo cell transportation
KW - Optical tweezers
KW - Zebrafish
KW - Closed-loop control
KW - Collision avoidance
KW - Disturbance compensation
KW - In vivo cell transportation
KW - Optical tweezers
KW - Zebrafish
KW - Closed-loop control
KW - Collision avoidance
KW - Disturbance compensation
KW - In vivo cell transportation
KW - Optical tweezers
KW - Zebrafish
UR - http://www.scopus.com/inward/record.url?scp=85092456994&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85092456994&origin=recordpage
U2 - 10.1016/B978-0-12-817463-0.00010-1
DO - 10.1016/B978-0-12-817463-0.00010-1
M3 - RGC 12 - Chapter in an edited book (Author)
SN - 9780128174630
SP - 281
EP - 328
BT - Control Systems Design of Bio-Robotics and Bio-Mechatronics with Advanced Applications
A2 - Azar, Ahmad Taher
PB - Academic Press
ER -